Predictor Of Coronary Heart Disease Research Articles

Higher non-HDL-cholesterol to HDL-cholesterol ratio linked with increased nonalcoholic steatohepatitis

BackgroundNon-HDL-cholesterol to HDL-cholesterol (non-HDL-c/HDL-c) ratio is a feasible predictor for coronary heart disease, metabolic syndrome, and insulin resistance. Patients with nonalcoholic steatohepatitis (NASH) have an increased risk of developing cardiovascular problems and type 2 diabetes. However, the predictive role of non-HDL-c/HDL-c ratio in NASH hasn’t been investigated yet.MethodsWe conducted a retrospective cohort study. A total of 3489 eligible subjects were selected in the present study. Prevalence and characteristics of NASH were demonstrated. Conditional logistic regression was used to analyze the association between non-HDL-c/HDL-c ratio and risks of NASH. Associations between non-HDL-c/HDL-c ratio and serum aminotransferase levels were also investigated.ResultsThe overall prevalence of NASH was 6.13%, higher in male (6.89%) than that in female (5.04%). Interestingly, the prevalence of NASH showed a positive correlation with the elevation of non-HDL-c/HDL-c ratio (Pearson’s Chi-squared test, linear trend 0.010, p < 0.05). The risk of NASH increased approximately 1.8-fold among subjects with higher non-HDL-c/HDL-c ratio. After adjustment for confounding factors, higher non-HDL-c/HDL-c ratio was still associated with a 54.4% increased risk of NASH. Male had higher risk of NASH than female when their non-HDL-c/HDL-c ratio increased. The risk of NASH in subjects with BMI more than 24 was 3 times higher than that in subjects with BMI less than 24. Every one unit increase in Non-HDL-c/HDL-c ratio was associated with 64.5% increase in ALT/AST level (p < 0.05) after adjustment for confounding factors.ConclusionsOur study provided strong evidence that subjects with higher non-HDL-c/HDL-c ratio had a higher risk of NASH, which suggested that non-HDL-c/HDL-c ratio might be a feasible predictor for NASH.

Association between neutrophil to lymphocyte ratio and severity of coronary artery disease

Background: Atherosclerosis is a chronic systemic inflammatory disease. Neutrophil-to-lymphocyte ratio (NLR) is systemic inflammatory marker that is correlated with poor cardiovascular outcome. The aim of this study was to investigate the association between neutrophil to lymphocyte ratio (NLR) and severity of coronary atherosclerosis.Methods: A total of 324 patients undergoing coronary angiography were included in the study. All the patients were included in study were divided into two groups based on the result of coronary angiography report. While 226 patients had abnormal coronary angiography (case) (78 female, mean age: 60.6±12.6 years), 98 patients had normal coronary angiography (control) (60 female, mean age: 57.2±10.9 years). NLR was calculated as the ratio of neutrophil count to lymphocyte count.Results: Although age distribution was similar between the two groups(p = 0.073), female gender was significantly higher in the normal coronary angiography group (p &lt; 0.001). Smoking history has shown a significant higher in cases compared to the normal coronary angiography (p=0.001). Patients with abnormal coronary angiography had significantly higher NLR when compared to patients with normal coronary angiography (p&lt;0.001). NLR was significantly correlated with Gensini score. In logistic regression analyses, NLR was an independent predictor of CAD. An NLR of 2.34 or higher predicted the CAD with a sensitivity of 66% and specificity of 70%.Conclusions: There is significant association between severity of coronary artery disease and neutrophils to lymphocyte ratio. This study suggests that the NLR is an independent predictor of coronary heart disease that may be useful for cardiac risk stratification in patients with coronary artery disease.

Basic vs More Complex Definitions of Family History in the Prediction of Coronary Heart Disease: The Multi-Ethnic Study of Atherosclerosis

ObjectiveTo determine whether family history of coronary heart disease (FH) definitions differ in their association with atherosclerotic cardiovascular disease (ASCVD) events. Patients and MethodsParticipants who provided FH data from July 17, 2000, through February 24, 2004, were identified. Definitions of FH were any, premature, and Familial Risk Assessment (FRA). Outcomes included coronary heart disease (CHD), stroke, peripheral artery disease, angina, and congestive heart failure. Multivariable-adjusted Cox models examined the association of FH definitions with events. C statistics and the net reclassification index examined the incremental prognostic contribution of each definition. ResultsIn 6200 participants, the proportions of any FH and premature FH were 36% and 16%, respectively, and of weak, moderate, and strong familial risk were 20%, 16%, and 20%, respectively. Over median follow-up of 10.1 years (range, 0.02-11.5 years), 741 participants experienced a composite event. Compared with no FH, any FH was associated with incident CHD, angina, and composite ASCVD (hazard ratios [95% CIs]: 1.4 [1.1-1.8], 1.6 [1.2-2.1], and 1.3 [1.1-1.5], respectively). Similar results were obtained for premature FH compared with no FH and for strong compared with weak FRA for these 3 outcomes. There was no association between the FH definitions and noncoronary cardiovascular events. Compared with traditional risk factors (C statistic = 0.740), any FH, premature FH, and FRA all improved discrimination of composite ASCVD (all P < .01); however, the differences in C statistics among any FH (0.743), premature FH (0.742), and FRA (0.744) were numerically small, as were differences in the net reclassification index. ConclusionA single question regarding the presence of FH in any first-degree relative performs just as well as more complicated assessments in predicting CHD. Trial Registrationclinicaltrials.gov Identifier: NCT00005487.

MACHINE LEARNING IN PREDICTING CORONARY HEART DISEASE AND CARDIOVASCULAR DISEASE EVENTS: RESULTS FROM THE MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA)

We aimed to evaluate whether machine learning (ML) approach will allow improved prediction as compared to standard coronary artery calcium (CAC) and clinical risk assessments in prediction of coronary heart disease (CHD) and atherosclerotic cardiovascular disease (ASCVD) events using the Multi-

The Correlation between Fat Consumption and Atherogenic Index on Type 2 Diabetes Melitus Patients in dr. Soebandi Hospital

One of the risk factor that can be changed in type 2 diabetes melitus is food consumption. Fat is one of the macronutrients that have significant influence in consumption. Unhealthy diet can be a trigger to macrovascular complication that is coronary heart disease (CHD) which started with atherosclerosis. Atherogenic index is a good predictor for CHD. This study aims to determine the correlation between fat consumption with atherogenic index in DMT 2 patients at RSD dr. Soebandi. This is an analitic observational study with cross sectional design, using 74 type 2 diabetes melitus patients from Internal Poly at RSD dr. Soebandi who met inclusion and exclusion criteria. Fat consumption were obtained with 24-hours food recall interview and atherogenic index were obtained from TG and HDL levels in medical record. The average of fat consumption is 34,01% and as much 33 subjects (44,6%) have high risk of CHD (AI&gt;0,21). Spearman correlation test between fat consumption with atherogenic index is p=0,025 which mean there is significant correlation between fat consumption and atherogenic index in type 2 diabetes melitus patients at RSD dr. Soebandi&#x0D; Keywords: DM Type 2, fat consumption, carbohydrate consumption, atherogenic index

Integrated genetic and epigenetic prediction of coronary heart disease in the Framingham Heart Study.

An improved method for detecting coronary heart disease (CHD) could have substantial clinical impact. Building on the idea that systemic effects of CHD risk factors are a conglomeration of genetic and environmental factors, we use machine learning techniques and integrate genetic, epigenetic and phenotype data from the Framingham Heart Study to build and test a Random Forest classification model for symptomatic CHD. Our classifier was trained on n = 1,545 individuals and consisted of four DNA methylation sites, two SNPs, age and gender. The methylation sites and SNPs were selected during the training phase. The final trained model was then tested on n = 142 individuals. The test data comprised of individuals removed based on relatedness to those in the training dataset. This integrated classifier was capable of classifying symptomatic CHD status of those in the test set with an accuracy, sensitivity and specificity of 78%, 0.75 and 0.80, respectively. In contrast, a model using only conventional CHD risk factors as predictors had an accuracy and sensitivity of only 65% and 0.42, respectively, but with a specificity of 0.89 in the test set. Regression analyses of the methylation signatures illustrate our ability to map these signatures to known risk factors in CHD pathogenesis. These results demonstrate the capability of an integrated approach to effectively model symptomatic CHD status. These results also suggest that future studies of biomaterial collected from longitudinally informative cohorts that are specifically characterized for cardiac disease at follow-up could lead to the introduction of sensitive, readily employable integrated genetic-epigenetic algorithms for predicting onset of future symptomatic CHD.

Nonfasting Apo-lipoprotein B and Triglyceride levels as a predictor of coronary heart disease in Type II diabetic patients.

Background & Objectives:Lipoprotein-A has been recognized as a risk factor for ischemic heart diseases. Myocardial infarction (MI) is common complication of ischemic heart disease. Diabetes play an incremental role in the development of coronary artery disease (CAD), however still there are conflicting data regarding the relationship of Lipoprotein-B and MI. We therefore wanted to evaluate the relationship of Lipo-B, MI and diabetes mellitus. Our objective was to determine the non-fasting Apo-lipoprotein B and triglycerides level among type II diabetic patients with ischemic heart disease and to compare with type II diabetic without ischemic heart disease.Methods:This was cross sectional study where two groups of patients were recruited in the study, Group-I included patient with Ischemic Heart Disease and diabetes while Group-II comprised of diabetes without Ischemic Heart Disease. Age, sex and basic demographic matching was done between the two groups. Data were collected using random sample. The comparative approach was used to see the role of diabetes in the elevation of Apo-lipoprotein B level, which is a risk factor for Ischemic heart diseases.Results:Two hundred forty eight patients (Cases: 123 Diabetic with myocardial infarction and (Control: 125 Diabetic without myocardial infarction) were included in the study. Mean Apo-B among diabetic patients with myocardial infarction was high (68.3±24.23 ng/ml) compared to non-cardiac patients (49.97±33.880 ng/ml) with a p <0.000. Marked difference was also observed in triglycerides levels where it was found very high (301.4±55.1 mg/dL) in patients of diabetes with myocardial infarction as compared to subjects without MI (137.7±84.7 mg/dL). There was positive correlation between Apo-lipoprotein and Triglycerides (P value=039).Conclusion:Based on the study result it was concluded that Apo-lipoprotein and triglycerides in diabetic patients with myocardial infarction, had higher levels compared to diabetic patients without Myocardial infarction and this could be a consequence of increase in age, insulin resistance and deficiency of insulin in the body. We also found positive correlation between Apo-lipoprotein and Triglycerides.

Cardiovascular Event Prediction by Machine Learning: The Multi-Ethnic Study of Atherosclerosis.

Machine learning may be useful to characterize cardiovascular risk, predict outcomes, and identify biomarkers in population studies. To test the ability of random survival forests, a machine learning technique, to predict 6 cardiovascular outcomes in comparison to standard cardiovascular risk scores. We included participants from the MESA (Multi-Ethnic Study of Atherosclerosis). Baseline measurements were used to predict cardiovascular outcomes over 12 years of follow-up. MESA was designed to study progression of subclinical disease to cardiovascular events where participants were initially free of cardiovascular disease. All 6814 participants from MESA, aged 45 to 84 years, from 4 ethnicities, and 6 centers across the United States were included. Seven-hundred thirty-five variables from imaging and noninvasive tests, questionnaires, and biomarker panels were obtained. We used the random survival forests technique to identify the top-20 predictors of each outcome. Imaging, electrocardiography, and serum biomarkers featured heavily on the top-20 lists as opposed to traditional cardiovascular risk factors. Age was the most important predictor for all-cause mortality. Fasting glucose levels and carotid ultrasonography measures were important predictors of stroke. Coronary Artery Calcium score was the most important predictor of coronary heart disease and all atherosclerotic cardiovascular disease combined outcomes. Left ventricular structure and function and cardiac troponin-T were among the top predictors for incident heart failure. Creatinine, age, and ankle-brachial index were among the top predictors of atrial fibrillation. TNF-α (tissue necrosis factor-α) and IL (interleukin)-2 soluble receptors and NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) levels were important across all outcomes. The random survival forests technique performed better than established risk scores with increased prediction accuracy (decreased Brier score by 10%-25%). Machine learning in conjunction with deep phenotyping improves prediction accuracy in cardiovascular event prediction in an initially asymptomatic population. These methods may lead to greater insights on subclinical disease markers without apriori assumptions of causality. URL: http://www.clinicaltrials.gov. Unique identifier: NCT00005487.

GW28-e0435 Prediction and intervention of coronary heart disease based on data mining

GW28-e0435 Prediction and intervention of coronary heart disease based on data mining

Serum Alanine Aminotransferase Level as a Risk Factor for Coronary Heart Disease Prediction in Koreans

Serum Alanine Aminotransferase Level as a Risk Factor for Coronary Heart Disease Prediction in Koreans

Inflow mapping method for numerical flow simulations of OCT-based patient-specific vessels using CFD

Abstract Alteration of the flow characteristics in coronary vessels is correlated with coronary heart disease (CHD). In particular, wall shear stress (WSS) appears to be a hemody-namic key factor in the genesis of CHD. Since computational fluid dynamics (CFD) is a well-known method for the inves-tigation of WSS, it may be a valuable tool for the prediction of CHD. Latest imaging techniques, such as optical coher-ence tomography (OCT) in conjunction with angiography deliver precise 2D data sets of patient-specific vessel geome-try, which can be used for CFD analysis. Current CFD stud-ies utilize patient-specific geometries, but are lacking well defined physiologic inflow conditions. In this study, we present an inflow mapping method for patient-specific arterial vessels, which is capable of consider-ing the influence of bifurcations located proximal of the OCT-data set. At first, the patient-specific vessel was recon-structed. For this purpose the OCT-based vessel cross sec-tions were arranged along an angiographic based vessel pathway. Secondly, we simulated the flow field in a generic bifurcation model by means of CFD. Thereafter the flow field of a side branch was extracted and transferred (mapped) to the inlet of the patient-specific vessel. To evaluate the influence of the physiological inlet the WSS distribution of the same patient-specific vessel was calculated using an axial-symmetric inflow condition. Analy-sis of the simulation data yielded deviations of the WSS distribution in the proximal vessel segment. A bifurcation, located upstream of the relevant vessel segment strongly affects the flow in the OCT-based vessel reconstruction and has a strong influence on the results of the numerical analy-sis. Therefore, it is important to implement not only the pa-tient-specific geometry, but also an inlet boundary condition adapted to the upstream velocity distribution reflecting the actual proximal flow situation of the vessel.

Fractional esterification rate of cholesterol in high-density lipoprotein associates with risk of coronary heart disease

BackgroundFractional esterification rate of cholesterol in high-density lipoprotein (FERHDL) has been found to be closely correlated with atherosclerotic dyslipidemia, especially lipoprotein distributions, and is a potentially useful predictor for coronary heart disease (CHD). The associations of FERHDL, measured by the simple and precise HPLC method, with angiographically defined CHD and its related risk factors in Chinese patients were evaluated.MethodsTwo hundred and fifty eight Chinese patients who had indications for angiography were enrolled in this study. Coronary angiograms were obtained by the standard techniques. FERHDL was determined by the HPLC method. Cholesterol levels in serum HDL, LDL and subfractions were measured by ultracentrifugation/HPLC method. Associations between FERHDL and CHD and CHD risk factors were analyzed.ResultsFERHDL was correlated with almost all the CHD risk factors. Compared with the non-CHD group, the CHD patients had higher values of FERHDL (20.9 ± 7.9%/h vs 17.7 ± 7.1%/h, p = 0.001). FERHDL was found to be independently and positively correlated with log TG (β = 0.386, P < 0.001) and log (LDLb-C) (β = 0.165, P = 0.020), respectively, and negatively correlated with log (HDL2-C)(β = −0.351, P < 0.001). Logistic regression analysis demonstrated that age, diabetes mellitus, smoking and FERHDL (OR = 1.056–1.080, p < 0.05) were independent risk factors for CHD.ConclusionFERHDL significantly correlated with both HDL2-C and LDLb-C, and therefore, is the predictor of lipoprotein distributions. In addition, after correcting for the presence of classic risk factors, FERHDL was independently associated with the presence of angiographically defined CHD.

Impact of CD14 polymorphisms on anti-apolipoprotein A-1 IGG-related coronary heart disease prediction in the general population

Aim: To determine whether autoantibodies to apolipoprotein A-1 (anti-apoA-1 IgG) predict incident coronary heart disease (CHD) in the general population, and whether this association is modulated by a functional CD14 receptor single-nucleotide polymorphism (SNP).

Relation of Carotid Intima-Media Thickness to Cardiovascular Events in Black Americans (From the Jackson Heart Study)

Although several prospective studies have reported independent relations between carotid intima-media thickness (CIMT) and risk of incident cardiovascular diseases (CVD) in primarily non-African-American (AA) cohorts, the utility of CIMT values for the prediction of incident coronary heart disease and stroke events in blacks remain unclear. At the baseline examination (2000 to 2004) of the Jackson Heart Study, AA adults 21 to 94 years of age (mean 54) underwent bilateral far-wall CIMT measurement (mean 0.76 mm). Incident CVD events were then assessed over 7 to 11 years of follow-up (2000 to 2011) from samples of 2,463 women (107 CVD events) and 1,338 men (64 CVD events) who were free of clinical CVD at baseline. Each 0.2-mm increase in CIMT was associated with age-adjusted incident CVD hazard ratios of 1.4 (95% confidence interval 1.2, 1.5) for women and 1.3 (1.1, 1.6) for men. Classification accuracy improved only slightly when comparing multivariable models that used traditional risk factors alone with models that added CIMT: C-statistics 0.837 (0.794, 0.881) versus 0.842 (0.798, 0.886) in women and 0.754 (0.683, 0.826) versus 0.763 (0.701, 0.825) in men. Similarly, risk reclassification was only mildly improved by adding CIMT: Net Reclassification Index 0.13 (p = 0.05) and 0.05 (p = 0.50) for women and men, respectively; Integrated Discrimination Improvement 0.02 (p = 0.02) and 0.01 (p = 0.26) for women and men, respectively. In conclusion, CIMT was associated with incident CVD but provided modest incremental improvement in risk reclassification beyond traditional risk factors in a community-based AA cohort.

3-year risk prediction of Coronary Heart Disease in hypertension patients: A preliminary study.

Hypertension is associated with increased morbidity and mortality in Coronary Heart Disease (CHD). However, the risk factors that cause hypertension patients develop into CHD remain unclear. This paper aims to study traditional and nontraditional risk factors of CHD in hypertension population. Data were extracted from the regional medical big data system of Shenzhen, a big city of China. In this study, we included 3395 hypertension patients aged from 30 to 79 years old. Among them, 1153 CHD events occurred within 3 years after they were first followed-up. A logistic regression model was used to evaluate the risk factors quantitatively and predict 3-year risk of CHD events. The results showed that traditional general-population-based CHD risk factors such as age, body mass index, diabetes, hyperlipemia, and chronic kidney disease still remained predictive in hypertension patients. In addition, the odds ratio (95% confidence interval) of CHD was 1.54 (1.19 to 2.01) for emotional or mental disorders, and 1.69 (1.21 to 2.34) for sleep disorders. And the model showed a good discriminative performance with an AUC of 0.839. It offered a new insight for hypertension patients that keeping psychological health and maintaining a good sleep quality could be helpful in preventing CHD. Given the high risk for CHD in patients with hypertension, control of these risk factors may have a substantial preventive effect on CHD.

Early short-term intensive multidisciplinary diabetes care: A ten-year follow-up of outcomes.

To evaluate the outcome of an early short-term intensive diabetic care program followed by a regular out-patient shared-care education program. We retrospectively reviewed the medical charts of 196 patients newly diagnosed with type 2 diabetes mellitus (DM) who were admitted to the hospital for intensive multidisciplinary interventions. For comparison, we also enrolled 206 patients with type 2 DM newly diagnosed but not receiving short-term intensive program. Both groups all attended an out-patient shared-care education program for more than one year. Outcome measure included average and standard deviation (SD) of glycated hemoglobin (HbA1c) over ten years, serum creatinine (Cr), lipid profile, urine albumin/Cr (UACR), and chronic diabetic complications after 10years later. The Kaplan-Meier event happening rates were used to compare the event rate of two samples. Multivariate Cox proportional-hazards models were used to investigate the influence of different variables on chronic complications. Patients who received short-term intensive diabetic education had less SD of HbA1cs: (0.7±0.7% vs. 1.0±0.8% (5.3±5.3mmol/mol vs 9.2±6.4mmol/mol), p<0.001), less new-onset coronary heart disease (CHD) (8.2% vs. 13.7%, p=0.005), lower serum Cr (1.4±0.7mg/dL vs. 1.5±0.9mg/dL, p=0.005), less progression of nephropathy was also revealed (13.5% vs. 21.2%, p=0.009) and lower UACR (4.7±1.4mg/g vs. 5.3±1.0mg/g, p<0.001). There were no group differences in age, gender distribution, average HbA1c, lipid profile, and new-onset of neuropathy and retinopathy. The independent predictors of CHD and nephropathy were short-term intensive diabetic education and SD of HbA1cs. Initiation of earlier intensive short-term multidisciplinary interventions in patients with newly diagnosed DM may decrease coronary heart disease and nephropathy. These better outcomes may be related to less fluctuation in blood glucose levels.

Lipoprotein (a) and Cardiovascular Risk: The Show Must go on.

Lipoprotein (a) [Lp(a)] is an independent but moderate, predictor for coronary heart disease (CHD) prevalence and severity. Several established and emerging cardiovascular (CV) risk factors including age, gender, ethnicity, smoking, dyslipidemia, hypertension, obesity, type 2 diabetes mellitus, alcohol consumption, arterial stiffness and hyperuricemia have been linked to Lp(a) metabolism. Apart from CHD, Lp(a) has been also associated with non-cardiac vascular diseases and diseases associated with increased CV risk such as chronic kidney disease, metabolic syndrome, non-alcoholic fatty liver disease, erectile dysfunction, obstructive sleep apnea syndrome, inflammatory bowel diseases and human immunodeficiency virus infection. The above data are discussed in the present narrative review. Several guidelines suggest the clinical use of Lp(a) in (re)defining vascular risk, especially in asymptomatic individuals at intermediate or high CV risk and those with a family history of premature CHD. By improving individuals risk stratification, Lp(a) may contribute to a better secondary prevention strategy. However, there is still a need to establish a standardized method to measure Lp(a) as well as selective potent therapies for lowering Lp(a). This will support conducting large randomized trials in order to establish whether lowering circulating Lp(a) levels will result in a significant reduction in CV events.

Abstract 426: Overexpression of Tissue-nonspecific Alkaline Phosphatase (TNAP) Accelerates Coronary Artery Disease in the Setting of Hypercholesterolemia in Mice

Objective: Vascular calcification in asymptomatic individuals is an independent predictor of coronary heart disease (CHD). It is therefore plausible that vascular calcification plays a direct pathophysiological role in atherosclerosis, an underlying cause of CHD. The purpose of this study was to examine the contribution that vascular calcification has on the development of coronary atherosclerosis in a mouse model of familial hypercholesterolemia. Approach and Results: Calcification was induced by overexpression of tissue-nonspecific alkaline phosphatase (TNAP) in endothelial cells of mice harboring a point mutation in the low density lipoprotein receptor ( ldlr, wicked high cholesterol, WHC). Mice were fed an atherogenic diet; echocardiographic and biochemical data were collected longitudinally. Atherosclerosis and vascular calcification were analyzed histologically in the aorta, aortic sinus and coronary arteries. TNAP mice were also treated with a combination of an atherogenic diet and a specific inhibitor of TNAP (SBI-425). Combined with the ldlr mutation and an atherogenic diet, TNAP-driven arterial calcification led to severe atherosclerosis with 100% morbidity characterized by occlusive coronary artery disease, pathological cardiac hypertrophy with dilated LV and reduced ejection fraction (EF). We detected an interaction between vascular calcification and atherosclerosis in mice with endothelial TNAP overexpression. This interaction was particularly prominent in coronary circulation. Targeting TNAP activity therapeutically helped improve survival and heart function of endothelial TNAP overexpressor mice, however the incomplete inhibition of TNAP by SBI-425 was a limitation of this study. Conclusions: Vascular calcification via TNAP overexpression in endothelial cells promotes coronary atherosclerosis and is pathogenic under conditions of hypercholesterolemia.

0088 RELATIONSHIPS BETWEEN SLEEP DISORDERED BREATHING AND CENTRAL AORTIC PRESSURE IN A COMMUNITY BASED POPULATION: THE TOON HELATH STUDY

Sleep-disordered breathing (SDB) has been developed as one of the risk factors for cardiovascular diseases. Recent studies suggest that central aortic pressure (CAP) could be a better predictor of coronary heart disease than brachial cuff blood pressure. However few population-based observational studies have shown the association between SDB and CAP. Thus, the objective of this study was to examine the association between SDB and CAP, using respiratory disturbance index (RDI) and snoring severity as an index of SDB. This cross-sectional study was conducted in the Toon Health Study between 2009 and 2012. The total number of 932 Japanese women and men aged 30 to 79 years were included in the analysis, excluding persons with missing values for RDI, CAP, snoring, and persons with history of hypertension, coronary heart disease, and stroke. RDI was estimated with one night sleep test using an airflow monitor. Subjects were grouped into 3 categories according to the levels of RDI: low (<10), moderate (10–20), high (>20). Snoring severity was estimated using a Berlin questionnaire, and subjects were grouped into 3 categories according to the levels of snoring: habitual snorers (snores nearly everyday, or 3–4 times a week), occasional snorers (snores 1–2 times a week, 1–2 times a month or nearly never), non-snorers (doesn’t snore). The CAP was measured using the HEM-9000 AI device, an automated tonometer. The association between RDI levels/snoring severity and CAP were analyzed using analysis of covariance and regression model. The persons with higher levels of RDI/habitual snoring tended to be male and to have higher BMI. Multivariable adjusted mean of CAP was significantly increased as the levels of RDI increased. (low:127.93mmHg, moderate:130.34 mmHg, high:132.43 mmHg, p for trend:0.01). However, the association was no longer significant after adjusted for BMI. Multivariable adjusted mean of CAP was significantly increased among snorers and it remained significant after adjusted for BMI. (habitual snorer:130.76 mmHg, occasional snorer:130.87 mmHg, non snorer: 127.58mmHg, p for difference:0.04). RDI was associated with CAP through BMI, whereas snoring severity was independently associated with CAP.

Correction.

HomeCirculation: Cardiovascular GeneticsVol. 10, No. 2Correction Free AccessCorrectionPDF/EPUBAboutView PDFSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessCorrectionPDF/EPUBCorrection Originally published18 Apr 2017https://doi.org/10.1161/HCG.0000000000000036Circulation: Cardiovascular Genetics. 2017;10:e000036This article corrects the followingClinical Utility of Multimarker Genetic Risk Scores for Prediction of Incident Coronary Heart DiseaseIn the article by Iribarren et al, “Clinical Utility of Multi-marker Genetic Risk Scores for Prediction of Incident Coronary Heart Disease: A Cohort Study among over 51 Thousand Individuals of European Ancestry,” which appeared in the December 2016 issue of the journal (Circulation: Cardiovascular Genetics. 2016;9:531–540), there was a style error in the title. “51 Thousand” should have been changed to “51 000.”The correction has been made online. The publisher regrets the error.DOI: 10.1161/HCG.0000000000000034 Previous Back to top Next FiguresReferencesRelatedDetailsRelated articlesClinical Utility of Multimarker Genetic Risk Scores for Prediction of Incident Coronary Heart DiseaseCarlos Iribarren, et al. Circulation: Cardiovascular Genetics. 2016;9:531-540 April 2017Vol 10, Issue 2 Advertisement Article InformationMetrics © 2017 American Heart Association, Inc.https://doi.org/10.1161/HCG.0000000000000036 Originally publishedApril 18, 2017 PDF download Advertisement